Author Archives: Dr. Vaibhav Kumar - Page 4
In this article, we will learn how to detect objects present in the images. For the detection of objects, we will use the YOLO (You Only Look Once) algorithm and demonstrate this task on a few images. In the result, we will get the image with captioned and highlighted objects with their probability of correct detection.
The post Hands-On Guide To Object Detection Using YOLO appeared first on Analytics India Magazine.
In this article, we will recognize the fruit where the Convolutional Neural Network will predict the name of the fruit given its image. We will train the network in a supervised manner where images of the fruits will be the input to the network and labels of the fruits will be the output of the network. After successful training, the CNN model will be able to correctly predict the label of the fruit.
The post Fruit Recognition using the Convolutional Neural Network appeared first on Analytics India Magazine.
Implementing AlexNet Using PyTorch As A Transfer Learning Model In Multi-Class Classification
In this article, we will employ the AlexNet model provided by the PyTorch as a transfer learning framework with pre-trained ImageNet weights. The network will be trained on the CIFAR-10 dataset for a multi-class image classification problem and finally, we will analyze its classification accuracy when tested on the unseen test images.
The post Implementing AlexNet Using PyTorch As A Transfer Learning Model In Multi-Class Classification appeared first on Analytics India Magazine.
Implementing AlexNet Using PyTorch As A Transfer Learning Model In Multi-Class Classification
In this article, we will employ the AlexNet model provided by the PyTorch as a transfer learning framework with pre-trained ImageNet weights. The network will be trained on the CIFAR-10 dataset for a multi-class image classification problem and finally, we will analyze its classification accuracy when tested on the unseen test images.
The post Implementing AlexNet Using PyTorch As A Transfer Learning Model In Multi-Class Classification appeared first on Analytics India Magazine.
In this article, we will discuss the architecture and implementation of AlexNet using Keras library without using transfer learning approach. In the end, we will evaluate the performance of this model in classification.
The post Hands-on Guide To Implementing AlexNet With Keras For Multi-Class Image Classification appeared first on Analytics India Magazine.
In this article, we will classify the sign language symbols using the Convolutional Neural Network (CNN). After successful training of the CNN model, the corresponding alphabet of a sign language symbol will be predicted. We will evaluate the classification performance of our model using the non-normalized and normalized confusion matrices. Finally, we will obtain the classification accuracy score of the CNN model in this task.
The post Hands-On Guide To Sign Language Classification Using CNN appeared first on Analytics India Magazine.
In this article, we will compare the multi-class classification performance of three popular transfer learning architectures - VGG16, VGG19 and ResNet50. These all three models that we will use are pre-trained on ImageNet dataset. For the experiment, we have taken the CIFAR-10 image dataset that is a popular benchmark in image classification. The performances of all the three models will be compared using the confusion matrices and their average accuracies.
The post Practical Comparison of Transfer Learning Models in Multi-Class Image Classification appeared first on Analytics India Magazine.
Here we will discuss how a professional certification like Chartered Data Scientist is different from a data science training. The Chartered Data Scientist is a self-study program where the aspirant needs to prepare on their own for the exam and hence, there is no need to attend any training for this.
The post How Is Chartered Data Scientist Program Different From The Data Science Training appeared first on Analytics India Magazine.
In this article, we will train the Deep Convolutional Generative Adversarial Network on Fashion MNIST training images in order to generate a new set of fashion apparel images.
The post Hands-On Guide To Deep Convolutional GAN for Fashion Apparel Image Generation appeared first on Analytics India Magazine.
In this article, we will see a comparison between two time-series forecasting models - ARIMA model and LSTM RNN model. Both of these models are applied in stock price prediction to see the comparison between them.
The post Comparing ARIMA Model and LSTM RNN Model in Time-Series Forecasting appeared first on Analytics India Magazine.